The SpaceML project aims to explore how organic molecules are created and broken down in space, using advanced machine learning techniques and computer simulations. Organic molecules, made up of carbon, hydrogen, and oxygen, are widespread in the universe and have been found from our own galaxy to the distant surroundings of the stars. Yet, questions about where these organic compounds come from and how they are synthesized remain unanswered. Therefore, SpaceML will use cutting-edge computational technologies to take this research further than ever before. The project will focus on three goals: Building machine-learning models to study how organic molecules behave under the harsh conditions found in space. Developing tools to predict the unique "fingerprints" of molecules, so we can match them to observations made by the telescopes. Simulating how molecules transform and react when exposed to radiation, helping us understand their life cycle in space.

2025

2029